Beyond the expectation–maximization (EM) algorithm for vector parameters, the EM for an unknown distribution function is often used in mixture models, density estimation, and signal recovery problems. We prove the convergence of the EM in functional spaces and show the EM likelihoods in this...

We address the problem of spherical deconvolution in a non-parametric statistical framework, where both the signal and the operator kernel are subject to measurement errors. After a preliminary treatment of the kernel, we apply a thresholding procedure to the signal in a second generation...

The aim of this article is to characterize the saturation spaces that appear in inverse problems. Such spaces are defined for a regularization method and the rate of convergence of the estimation part of the inverse problem depends on their definition. Here we prove that it is possible to define...